Hi all, I'd like to put ob-stan.el (attached) in the contrib directory. It adds support for the Stan [1] programming language. I wrote it a while back, but a recent post on the Stan ML [2] made me think that others may find it useful (although I'd guess that the intersection of Stan and Org users is quite small). It's short because the only output that really makes sense is to dump the contents to a file (and maybe compile it), which is then used by a downstream interface [3].
Please let me know if you have any comments about the implementation or if you don't think contrib directory is a good place for it. Thanks. [1] http://mc-stan.org/ [2] https://groups.google.com/d/msg/stan-users/m4r8iUNiLug/Gexo8qCIBgAJ [3] http://mc-stan.org/interfaces/ -- Kyle
ob-stan.el
Description: application/emacs-lisp
* With RStan
#+name: normal-stan
#+begin_src stan :file model.stan
data {
int<lower=1> N;
vector[N] x;
}
parameters {
real mu;
real<lower=0> std;
}
model {
x ~ normal(mu, std);
}
#+end_src
#+RESULTS: normal-stan
[[file:model.stan]]
#+begin_src R :session *R* :var model=normal-stan :results silent
library(rstan)
N <- 50
x <- rnorm(N, 20, 3)
fit <- stan(file=model, data=list(N=N, x=x))
#+end_src
* With CmdStan
#+begin_src elisp :results silent
(setq org-babel-stan-cmdstan-directory "~/src/cmdstan/")
#+end_src
#+name: normal-compile
#+begin_src stan :file normal
data {
int<lower=1> N;
vector[N] x;
}
parameters {
real mu;
real<lower=0> std;
}
model {
x ~ normal(mu, std);
}
#+end_src
#+RESULTS: normal-compile
[[file:normal]]
#+begin_src R :session *R* :results silent
stan_rdump(c('N', 'x'), 'normal.data.R')
#+end_src
#+begin_src sh :results output drawer
./normal sample data file=normal.data.R
#+end_src
#+RESULTS:
:RESULTS:
method = sample (Default)
sample
num_samples = 1000 (Default)
num_warmup = 1000 (Default)
save_warmup = 0 (Default)
thin = 1 (Default)
adapt
engaged = 1 (Default)
gamma = 0.050000000000000003 (Default)
delta = 0.80000000000000004 (Default)
kappa = 0.75 (Default)
t0 = 10 (Default)
init_buffer = 75 (Default)
term_buffer = 50 (Default)
window = 25 (Default)
algorithm = hmc (Default)
hmc
engine = nuts (Default)
nuts
max_depth = 10 (Default)
metric = diag_e (Default)
stepsize = 1 (Default)
stepsize_jitter = 0 (Default)
id = 0 (Default)
data
file = normal.data.R
init = 2 (Default)
random
seed = 1573443700
output
file = output.csv (Default)
diagnostic_file = (Default)
refresh = 100 (Default)
Gradient evaluation took 4e-06 seconds
1000 transitions using 10 leapfrog steps per transition would take 0.04 seconds.
Adjust your expectations accordingly!
Iteration: 1 / 2000 [ 0%] (Warmup)
Informational Message: The current Metropolis proposal is about to be rejected
because of the following issue:
stan::prob::normal_log: Scale parameter is 0, but must be > 0!
If this warning occurs sporadically, such as for highly constrained variable
types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely
ill-conditioned or misspecified.
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# Elapsed Time: 0.013356 seconds (Warm-up)
# 0.024708 seconds (Sampling)
# 0.038064 seconds (Total)
:END:
